VEIN model and future integration with MUSICA

Sergio Ibarra-Espinosa¹ ²

1 CIRES, University of Colorado-Boulder

2 GML, National Oceanic and Atmospheric Administration (NOAA)

VEIN model and future integration with MUSICA

- Sergio Ibarra-Espinosa¹'²
- 1 CIRES, University of Colorado-Boulder
- 2 GML, National Oceanic and Atmospheric Administration (NOAA)
- sergio.ibarra-espinosa@noaa.gov

- Presentation for MUSICA group, ACOM/NCAR

drawing drawing drawing drawing drawing

Introduction (2014)

Intro

Why do we need MUSICA?

Empirical and modeling studies have provided strong evidence of dynamical and chemical coupling across the range of spatial and temporal scales inherent in the Earth System. Current models, however, are inadequate in accounting for the two-way coupling of the range of relevant scales from street-level to regional to global and from the surface up to the mesosphere.

vein

Characteristics

Process

  • Top down (POLYGON) and bottom-up (LINESTRING)
  • Activity adjusted by fuel consumption
  • Activity and emission factors by age of use
  • Includes methodolologies for China, US/EPA (MOVES), Brazil and Europe.
  • Gridded emissions with any polygon shape
  • Includes more than 10 chemical mechanisms

Atmoschem Software

  • eixport reads spatial emissions and generates inptus for air quality models - such as WRF CHEM
  • respeciate Port the US/EPA Speciate 5.0 to R (no need of MS Access)
  • cptcity (7120 colour palettes from cptcity web archive)

Some applications

Formaldehyde: 0.059 Mt/y

NP 50 nm: 1.58E+26 /y

NorthEast China

drawing

Applications: Sao Paulo

library(sf)
library(vein)
x <- readRDS("rds/CO.rds")
g <- st_sf(
  geometry = st_make_grid(
    x = x,
    cellsize = 3000, 
    square = F))
co <- emis_grid(spobj = x,
                g = g)
## Sum of street emissions 1080803725.33
## Sum of gridded emissions 1080803725.33

WRF Chemi using eixport

Integration with US/EPA MOVES

Recent Research: Integration of MOVES and VEIN:

  • MOVES is the official vehicular emissions model for US. Runs on Windows, written in Java/SQL with MariaDB. VEIN is very versatile, ideal for traffic flow at streets. Currently has two approaches:
  • 1 Estimation using Windows with MOVES >3.0 installed. Emission factors are accessed using SQL in R.
  • 2 Estimation using any OS. Emission factors are exported from Windows as .csv.gz and read with data.table::fread.
  • Paper will be submitted to GMD (under development)

Screenshots

vein::get_project(directory = "sacramento", case = "moves")

Sacramento County 2017

  • Traffic flow for a 4-stage travel demand model output for Sacramento Area, extracted for Sacramento County.’
  • Traffic flow is for 2016 from CARB.
  • Traffic flow is total traffic volume 08:00-09:00.
  • Vehicular composition based on baltimore.
  • Fuel consumption for 2017.
  • Emission factors from Baltimore 2017.
  • Temporal factors from hourly VMT MOVES Baltimore.
  • Assumed BPR parameters.

Speed parameters

Emissions

Spatial Emissions

## Sum of street emissions 10466599.96
## Sum of gridded emissions 10466599.96

Some advances using MUSICA

MUSICA run over South America

Geometry

  • The idea is to re-construct geometry from the NetCDF file.
  • Generate Well Known Text POLYGON, example:
POLYGON ((274.6966 -59.03607, 274.8997 -59.00577, 274.9453 -58.88916, 274.7924 -58.79595, 274.5942 -58.8158, 274.5485 -58.93235, 274.5485 -58.93235, 274.5485 -58.93235, 274.5485 -58.93235, 274.5485 -58.93235, 274.6966 -59.03607))

Vertex:

nc <- nc_open("/glade/p/cgd/amp/patc/GRID_REPO/ne0np4.SAMwrf01.ne30x2/grids/SAMwrf01_ne30x2_np4_SCRIP.nc")
lat <- ncdf4::ncvar_get(nc, "grid_corner_lat")
lat <- rbind(lat, lat[1, i])

lon <- ncdf4::ncvar_get(nc, "grid_corner_lon")
lon <- rbind(lon, lon[1, i])
geo <- sf::st_polygon(list(cbind(lon, lat)))

Time series

2014-08-18

VEIN emissions

VEIN emissions

Gracias!

- https://ibarraespinosa.github.io/
- sergio.ibarra-espinosa@noaa.gov
- https://scholar.google.com.br/citations?user=8ohZGHEAAAAJ
- https://github.com/ibarraespinosa
- https://www.researchgate.net/profile/Sergio_Ibarra-Espinosa
- https://orcid.org/0000-0002-3162-1905